code: def build_model(data, mean_function):
      model = GPR(data, kernel=RBF(), mean_function=mean_function)
      set_trainable(model.kernel, False)
      model.likelihood.variance.assign(1e-2)
      set_trainable(model.likelihood, False)
      return model
  
file_path: GPflow/notebooks/tailor/external-mean-function.pct.py
imports: import matplotlib.pyplot
  import numpy
  import tensorflow
  import gpflow
  from gpflow.ci_utils import reduce_in_tests
  from gpflow.kernels import RBF
  from gpflow.models import GPR
  from gpflow.config import default_float
  from gpflow import set_trainable
  import time
label_desc: Use image node_id 4 for calling a global function with example usage: build_model(data, mean_function) and returns: model